Main Implementation of kd-Tree in MATLAB
The implementation of kd-tree in MATLAB primarily consists of 4 core subfunctions
MATLAB Source Code for Object Tracking Implementation
Object tracking source code implemented in MATLAB, containing three core sub-functions with optimized performance for various applications including drones and robotics.
MATLAB Implementation of Genetic Algorithm with Code Optimization Features
A comprehensive MATLAB genetic algorithm program featuring modular sub-functions, adaptive multidimensional matrix parameter solving, floating-point real number optimization, and clearly structured code for easy understanding and implementation.
Professor Zhou Donghua's Strong Tracking Filter
Professor Zhou Donghua's Strong Tracking Filter program package includes two utility subfunctions and three main programs designed for different object models. All programs are error-free and can be directly executed to generate output plots.
Cross-Validation Subfunction for Parameters c and g in libsvm
Implementation and methodology for cross-validation of libsvm parameters c and g with code integration approaches
Ultra-Wideband Signal Analysis
UWB Analysis: Essential Subfunctions for Ultra-Wideband Signal Processing - Part 6
Two-Dimensional Wavelet Transform (Forward and Inverse) in MATLAB Environment
Implementation of 2D wavelet transform (forward and inverse) using two-dimensional convolution in MATLAB, featuring a sub-function for generating wavelet coefficients (including both decomposition and reconstruction coefficients). Users can extend functionality by adding custom coefficients.
MATLAB Subfunctions for Multipath Channel Modeling
Implementation of MATLAB subfunctions for multipath channels, including Jakes model and other channel modeling approaches with code implementation details
Simulation Study of Kalman Filter in Target Tracking Applications
Simulation study of Kalman filter applications in target tracking. Subfunctions implement Kalman filtering for tracking moving target positions, while the main function performs tracking based on specific assumptions and Monte Carlo simulations. Scenario setup: A two-coordinate radar observes a target moving on a plane with constant velocity motion along the x-axis at 15 m/s from 0-600 seconds, starting from (-10000 m, 2000 m). Radar scan period T=2 seconds, with independent x and y observations having observation noise standard deviation of 100 meters each.
OFDM Water-Filling Algorithm MATLAB Simulation Code
MATLAB simulation code for OFDM water-filling algorithm enabling system simulation with sub-functions for comprehensive communication system analysis